EyeArt v2.2.0

K223357

Eyenuk, Inc. · cleared 2023-06-16 · product code PIB · Ophthalmic

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“EyeArt is a software as a medical device that consists of three components – Client, Server, and Analysis Computation Engine (Figure 1).”
Algorithmensemble of clinically aligned machine learning (including deep learning) algorithms
source quote (p.5)
“EyeArt Analysis Computation Engine: This component analyzes the images to determine exam quality and detect mtmDR and vtDR. It consists of an ensemble of clinically aligned machine learning (including deep learning) algorithms.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedYes
source quote (p.8)
“EyeArt also implements comprehensive cybersecurity measures for data confidentiality, data integrity, and data and service availability. Designed to meet industry standard cybersecurity best practices, EyeArt ensures that data remains secure (with encryption during transit and at rest) and private (with authentication and authorization protocols enabling access).”

Validation studies (2)

Prospective clinical

n=171 patients · 6 site(s)

endpoints: diagnostic accuracy; precision

standards: Early Treatment for Diabetic Retinopathy Study (ETDRS) severity scale

Retrospective clinical

n=655 patients · 6 site(s)

endpoints: sensitivity; specificity; imageability; positive predictive value (PPV); negative predictive value (NPV)

standards: Early Treatment for Diabetic Retinopathy Study (ETDRS) severity scale

Reported performance (6 observations)

sensitivity0.959CI 90.4% - 100%
source quote (p.9)
“95.9% [90.4% - 100%] (70/73)”
specificity0.864CI 81.2%- 91.1%
source quote (p.10)
“86.4% [81.2%- 91.1%] (216/250)”
ppvas written: “Positive Predictive Value (mtmDR)”0.673CI 55.9% - 77.4%
source quote (p.10)
“67.3% [55.9% - 77.4%] (70/104)”
npvas written: “Negative Predictive Value (mtmDR)”0.986CI 96.9% - 100%
source quote (p.10)
“98.6% [96.9% - 100%] (216/219)”
ppvas written: “Positive Predictive Value (vtDR)”0.556CI 39.2% - 72.0%
source quote (p.10)
“55.6% [39.2% - 72.0%] (30/54)”
npvas written: “Negative Predictive Value (vtDR)”0.996CI 98.8% - 100%
source quote (p.10)
“99.6% [98.8% - 100%] (266/267)”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

0
recalls in product code, 24mo
0
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
0
drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Ophthalmic panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K223357